Weak Antilocalization and Spin Precession in Quantum Wells
W.Knap, C.Skierbiszewski, A.Zduniak, E. Litwin-Staszewska, D.Bertho,, F. Kobbi, J. L. Robert (Montpellier, France), G. E. Pikus (St. Petersburg,, Russia), F. G. Pikus (Santa Barbara, CA, USA), S. V. Iordanskii (Moscow,, Russia), V. Mosser (Montrouge, France)

TL;DR
This paper investigates how spin splitting affects weak localization in GaInAs quantum wells through magnetoconductivity measurements, developing a comprehensive theory that accounts for various spin splitting contributions and matching experimental data.
Contribution
The paper introduces a theory that incorporates both linear and cubic spin splitting terms in quantum wells, improving understanding of their influence on weak localization effects.
Findings
Different spin splitting terms significantly influence magnetoconductivity.
All three contributions are comparable within the studied electron density range.
The results help identify dominant spin relaxation mechanisms and refine spin splitting parameters.
Abstract
The results of magnetoconductivity measurements in GaInAs quantum wells are presented. The observed magnetoconductivity appears due to the quantum interference, which lead to the weak localization effect. It is established that the details of the weak localization are controlled by the spin splitting of electron spectra. A theory is developed which takes into account both linear and cubic in electron wave vector terms in spin splitting, which arise due to the lack of inversion center in the crystal, as well as the linear terms which appear when the well itself is asymmetric. It is established that, unlike spin relaxation rate, contributions of different terms into magnetoconductivity are not additive. It is demonstrated that in the interval of electron densities under investigation (0.98-1.85)*10^(12) 1/cm^2 all three contribution are comparable and have to be taken into account to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
